There was a time when anything that could be done on a computer could be done faster on a supercomputer. However, because supercomputers could address challenges that were well beyond the capabilities of ordinary computers, they became increasingly specialized, with emphasis on compute-bound problems, making them somewhat less suitable for general purpose computing. Business computers also evolved, while retaining their general purpose nature, and also became faster. In order to address a broader range of high-performance computing (HPC) needs, supercomputers need to become more general purpose, because the largest potential HPC markets are, by far, associated with business needs. Likewise, to address those large potential HPC markets, business computers need to gain much more performance. Finally, the largest potential HPC markets are likely to remain unaddressable until the associated needs can be met, and one of the key needs is affordability.
There is an ongoing and increasing demand, possibly an insatiable demand, for affordable computer processing power. Supercomputers—or alternatively, high-performance computing (HPC) systems—have historically been very expensive, and thus confined to a relatively small set of applications (e.g., weather modeling, academic and government-based research, etc.) paid for by well-funded customers and users, and thus have been out of reach of many potential customers. The customer set has been so limited that for many years the highest performing systems have been tracked on a list presently known as the “Top 500” (www.top500.org). Such a list would not be practical if even a reasonable fraction of the customers who could take advantage of supercomputers actually purchased and operated them.
The potential market for supercomputers is essentially untapped, primarily because it is mostly not addressable with the supercomputers available today (nor is it apparently addressable with today's business servers, including “mainframes”).
Today's supercomputers and business servers not only miss the mark in terms of affordability, but also in terms of their fitness for purpose. While there are clearly a few enterprise applications that are a good fit for supercomputers as they are presently designed, the large majority of commercial applications are not a good fit at present, partly due to a requirements mismatch. While business servers are already better-suited to running today's commercial applications, they cannot provide the computer power needed for the next generation of HPC-class business applications. Ultimately, the vendors of supercomputers and business servers are both racing to address the same markets, but from different starting points . . . .
Beyond the applications themselves, there are very real issues associated with achieving high levels of affordable system survivability, disaster recovery, and security (including data confidentiality integrity, availability, etc.), which (we assert) are not addressed well by any contender:                The costs of electricity to power a datacenter exceeds the costs of the datacenter itself, and the cost of power is not only not going down, but is anticipated to rise sharply over the next few decades.        Datacenters rarely store more than 72 hours worth of fuel, so they typically contract with local fuel suppliers to commence refueling deliveries within 24 hours of an extended power outage. In the event of a regional disaster that drops the utility power grids and renders key roads impassable, timely fuel delivery is unlikely. Of course, the contracted fuel sources may also be out of commission.        The actual power densities of datacenters may, sooner or later, exceed their intended designs, due to increased electronics density (the trend toward smaller, lower-power chips is offset by the insatiable demand for computing power).        There's an increased awareness of the need for the conservation of non-renewable resources, and vendors are striving to produce equipment that consumes less energy. The current reality is that heat energy rejected into the atmosphere by datacenters is simply wasted.        Datacenters represent a high concentration of assets, and thus make excellent targets for thieves, espionage, and terrorists.        With few exceptions, typical “manned” or “guarded” datacenters are designed to prevent the unauthorized admission of anyone who is not carrying a weapon. However, typical security staff present little deterrent to armed attackers, much less to well-organized, well-funded attackers with armed with inside information, tools, and automatic weapons—thus, the claimed security associated with typical hardened datacenters is illusory.        Datacenters represent a single point of failure (the datacenter itself), regardless of the level of internal redundancy. Thus, a single regional disaster or terrorist attack may effectively destroy companies whose livelihood depends on a failed (or destroyed) datacenter. Of course, a datacenter may fail without actually being attacked.        “There are two kinds of datacenters; those which have failed, and those that will.”        Despite a general awareness of Byzantine failure scenarios, disaster recovery preparedness rarely extends beyond having one or two backup datacenters, if any. Synchronously connected datacenters typically must be colocated relatively nearby (e.g., 10 to 60 miles is typical, with 300 miles or so as an upper limit), which means they may be subject to the same regional threats, and thus, simultaneous failures. Asynchronously connected datacenters may be geographically located at arbitrary distances, but may lag in data currency. Also, if Byzantine failures are considered, and a datacenter is taken as a single process, backed up by others coordinating asynchronously, then accommodating a single faulty datacenter would require a minimum of four data centers (i.e., 3f+1, where f is the number of faulty datacenters to be tolerated).        
Collectively, these concerns bring us back to affordability, not only in terms of capital expense (i.e., the cost of asset acquisition), but more importantly, the operational expense. It is well-known in the industry that, despite the fact that the acquisition cost of supercomputing assets is very high, it is quickly surpassed by the cost of operating those assets. Together, these asset acquisition and operational costs comprise the total cost of ownership (TCO), which is a key factor in any return-on-investment (ROI) calculation. However, as we move forward, the trend toward an increased demand for supercomputing may not be merely to achieve a particular ROI, but rather, to survive. If done right, which includes affordability as a prerequisite, supercomputing may enjoy network effects and become indispensable (i.e., highly competitive companies may, in all likelihood, need access to supercomputing), and ROI may become far less relevant, making the buying decision a more obvious choice. Thus, for the addressable markets, affordable supercomputing may become a necessary component in the business survival kit.
Summary of Key Problems with Datacenters Today (all are addressed by SHADOWS and SUREFIRE):                High acquisition cost (space/real estate, construction, equipment, integration)        High and accelerating power consumption        Sprawling layouts, high space requirements        Physical security becoming less effective        Requires manpower, operational overhead        
Mediocre survivability (many vulnerabilities)                Concentration of assets increases risk (makes datacenters an important target, etc.)        Heterogeneous, difficult-to-manage mix of everything (computers, network gear, power, cooling, etc.)        